• Journal of Biosystems Engineering
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• v.35 no.2
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• pp.124-131
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• 2010

Chlorophyll fluorescence has been researched for assessing fruit post-harvest quality and condition. The objective of this preliminary research was to investigate the potential of fluorescence spectroscopy for measuring apple fruit quality. Ultraviolet (UV) and blue light was used as an excitation source for inducing fluorescence in apples. Fluorescence spectra were measured from 'Golden Delicious' (GD) and 'Red Delicious' (RD) apples using a visible/near-infrared spectrometer after one, three, and five minutes of continuous UV/blue light illumination. Standard destructive tests were performed to measure fruit firmness, skin and flesh color, soluble solids and acid content from the apples. Calibration models for each of the three illumination time periods were developed to predict fruit quality indexes. The results showed that fluorescence emission decreased steadily during the first three minutes of UV/blue light illumination and was stable within five minutes. The differences were minimal in the model prediction results based on fluorescence data at one, three or five minutes of illumination. Overall, better predictions were obtained for apple skin chroma and hue and flesh hue with values for the correlation coefficient of validation between 0.80 and 0.90 for both GD and RD. Relatively poor predictions were obtained for fruit firmness, soluble solids content, titrational acid, and flesh chroma. This research has demonstrated that fluorescence spectroscopy is potentially useful for assessing selected quality attributes of apple fruit and further research is needed to improve fluorescence measurements so that better predictions of fruit quality can be achieved.

• Journal of Korean Society on Water Environment
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• v.30 no.4
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• pp.409-417
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• 2014

Spatial prediction methods have been useful to determine the variability of water quality in space and time due to difficulties in collecting spatial data across extensive spaces such as watershed. This study compares two kriging methods in predicting BOD concentration on the unmonitored sites in the Geum River Watershed and to assess its predictive performance by leave-one-out cross validation. This study has shown that cokriging method can make better predictions of BOD concentration than ordinary kriging method across the Geum River Watershed. Challenges for the application of cokriging on the spatial prediction of surface water quality involve the comparison of network-distance-based relationship and euclidean-distance-based relationship for the improvement in the predictive performance.

• Journal of Climate Change Research
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• v.9 no.1
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• pp.81-90
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• 2018

"The Framework Act on Low-Carbon Green Growth" specifies the requirements for the development and verification of emission factors for establishing reliable national greenhouse gas statistics. The scope of the regulations covers the development and validation of energy, industrial processes, solvents and other product use, agriculture, land use, land use change and emission and absorption coefficients of the forestry and waste sector as defined in the 1996 IPCC Guideline and GPG 2000, The minerals sector to be covered in this study belongs to industrial processes. As a representative method for quantifying and evaluating GHG emission factors, there are emission grade quality grading and DARS (Data Rating Rating System) in the 'Procedures for Preparing Emission Factor Documents (1997)' reported by US-EPA. However, the above two methods are not specific and comprehensive, and lack the details for accurate emission factor verification. Therefore, there is a need for a method for verifying and quantifying certified greenhouse gas emission factors that reflects characteristics of each industry sector in Korea and accord with IPCC G/L and GHG target management. In this study, we conducted a weighted study on quantitative and evaluation lists of emission factor using questionnaires to develop a more accurate methodology for quantifying national greenhouse gas emission factors in the mineral sector. Quantification and evaluation of emission factor are classified into essential verification and quality evaluation. The essential verifications are : administrative compatibility, method of determining emission factors, emission characteristics, sampling methods and analysis methods, representativeness of data. The quality evaluations consisted of the quality control of the data, the accuracy of the measurement and analysis, the level of uncertainty, not directly affect the emission factor, but consisted of factors that determine data quality.

• Journal of Environmental Science International
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• v.25 no.1
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• pp.181-190
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• 2016

Regional air quality regulation is a system that allows the Minister of Environment to designate the local area as air quality control region where the concentrations of air pollutants are exceeding the environmental standards, and the local governments that administrate the regulated area have to develop and practise a plan for reducing the air pollutants. From the data observed yearly by the monitoring stations in 8 provincial cities with more than 0.5 million people was judged the compliance with air quality standards in each municipality for the period of 2003 to 2013. As the result of investigation on air pollutants concentrations of each city, it was found that there was no station that exceeds the ambient air quality standards of CO, $SO_2$ and 24-hour $NO_2$. But all municipalities exceeded the standards of 8-hour $O_3$, annual and 24-hour $PM_{10}$, and therefore 8 municipalities can be designated to be under the local air regulation. For the annual $NO_2$ were the monitoring sites necessary requirements for designation of the air quality regulation region in Cheongju, Cheonan, Daejeon and Gwangju area. Incase of 1-hour $O_3$, some of stations in Pohang, Cheongju, Cheonan and Changwon area were over the designation standards for the air quality control region.

• Spatial Information Research
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• v.21 no.2
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• pp.45-54
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• 2013

Analytical and simulation error models have the ability to describe (or realize) error-corrupted versions of spatial data. But the different approaches for modeling positional errors require an internal validation that ascertains whether the analytical and simulation error models predict correct positional errors in a defined set of conditions. This paper presents stochastic simulation models of a point and a line segm ent to be validated w ith analytical error models, which are an error ellipse and an error band model, respectively. The simulation error models populate positional errors by the Monte Carlo simulation, according to an assumed error distribution prescribed by given parameters of a variance-covariance matrix. In the validation process, a set of positional errors by the simulation models is compared to a theoretical description by the analytical error models. Results show that the proposed simulation models realize positional uncertainties of the same spatial data according to a defined level of positional quality.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2019.10a
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• pp.87-87
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• 2019

The consumption of herbal medicine and related products (herbal products) have increased in South Korea. At the same time the quality, safety, and efficacy of herbal products is being raised. Currently, the herbal products are standardized and controlled according to the requirements of the Korean Pharmacopoeia, the National Institute of Health and the Ministry of Public Health and Social Affairs. The validation of herbal products and their medicinal component is important, since many of these herbal products are composed of two or more medicinal plants. However, there are no tools to support the validation process. Interest in deep learning has exploded over the past decade, for herbal medicine using algorithms to achieve herb recognition, symptom related target prediction, and drug repositioning have been reported. In this study, individual images of four herbs (Panax ginseng C.A. Meyer, Atractylodes macrocephala Koidz, Poria cocos Wolf, Glycyrrhiza uralensis Fischer), actually sold in the market, were achieved. Certain image preprocessing steps such as noise reduction and resize were formatted. After the features are optimized, we applied GoogLeNet_Inception v4 model for herb image recognition. Experimental results show that our method achieved test accuracy of 95%. However, there are two limitations in the current study. Firstly, due to the relatively small data collection (100 images), the training loss is much lower than validation loss which possess overfitting problem. Secondly, herbal products are mostly in a mixture, the applied method cannot be reliable to detect a single herb from a mixture. Thus, further large data collection and improved object detection is needed for better classification.

• Journal of the Korean Society of Radiology
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• v.17 no.5
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• pp.709-715
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• 2023

In this study, the performance evaluation of image quality for noise reduction was implemented using the U-net deep learning architecture in computed tomography (CT) images. In order to generate input data, the Gaussian noise was applied to ground truth (GT) data, and datasets were consisted of 8:1:1 ratio of train, validation, and test sets among 1300 CT images. The Adagrad, Adam, and AdamW were used as optimizer function, and 10, 50 and 100 times for number of epochs were applied. In addition, learning rates of 0.01, 0.001, and 0.0001 were applied using the U-net deep learning model to compare the output image quality. To analyze the quantitative values, the peak signal to noise ratio (PSNR) and coefficient of variation (COV) were calculated. Based on the results, deep learning model was useful for noise reduction. We suggested that optimized hyper parameters for noise reduction in CT images were AdamW optimizer function, 100 times number of epochs and 0.0001 learning rates.

• Aerospace Engineering and Technology
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• v.12 no.2
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• pp.30-39
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• 2013

In this study, calibration processes and methods of evaluating the radiometric quality of satellite images from the meteorological payload on the GEO-KOMPSAT-2A were described. MTF(Modulation Transfer Function), SNR(Signal-To-Noise Ratio), NEdT(Noise Equivalent Delta Temperature), and Dynamic Range, which are the major parameters for assessment of data radiometric quality of space-borne visible and infrared sensors, are focused. Key process of the quality check of the satellite data is the comparing the image radiometric performance parameters during the In-Oribit Test with those acquired from the ground tests. Validation plan of the image quality of the GEO-KOMPSAT-2A Meteorological Imager is addressed based on the analyses results of COMS MI data during the COMS In-Orbit Test period

• Bulletin of the Korean Chemical Society
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• v.32 no.5
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• pp.1547-1553
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• 2011

An effective analytical method of gas chromatography/mass spectrometry (GC/MS) was developed for the rapid determination of essential oils in the crude extract of Acorus species (Acorus gramineus, Acorus tatarinowii, and Acorus calamus). Major phenypropanoids (${\beta}$,${\alpha}$-asarone isomers, euasarone, and methyleugenol) and ${\beta}$-caryophyllene in Acorus species were used as marker compounds and determined for the quality control of herbal medicines. To extract marker compounds, various extraction techniques such as solvent immersion, mechanical shaking, and sonication were compared, and the greatest efficiency was observed with sonication extraction using petroleum ether. The dynamic range of the GC/MS method depended on the specific analyte; acceptable quantification was obtained between 10 and 2000 ${\mu}g/mL$ for ${\beta}$-asarone, 10 and 500 ${\mu}g/mL$ for ${\alpha}$-asarone, 10 and 200 ${\mu}g/mL$ for methyleugenol, and between 5 and 100 ${\mu}g/mL$ for ${\beta}$-caryophyllene. The method was deemed satisfactory by inter- and intra-day validation and exhibited both high accuracy and precision, with a relative standard deviation < 10%. Overall limits of detection were approximately 0.34-0.83 ${\mu}g/mL$, with a standard deviation (${\sigma}$)-to-calibration slope (s) ratio (${\sigma}$/s) of 3. The limit of quantitation in our experiments was approximately 1.13-3.20 ${\mu}g/mL$ at a ${\sigma}$/s of 10. On the basement of method validation, 20 samples of Acorus species collected from markets in Korea were monitored for the quality control. In addition, principal component analysis (PCA) and hierarchical cluster analysis (HCA) were performed on the analytical data of 20 different Acorus species samples in order to classify samples that were collected from different regions.

• Journal of Society of Preventive Korean Medicine
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• v.20 no.3
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• pp.45-53
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• 2016

Objectives : The number of people in Mibyeong state that complain of physical and mental discomfort but without a clear medical diagnosis has rapidly increased, but the conventional medical system is insufficient to care for these people. By establishing an evaluation instrument for Mibyeong state, it will be possible to provide a research base for Mibyeong management system and expand the clinical area of integrative medicine. Methods : Mibyeong Index was designed to measure inconvenience and resilience of subject's complains including four physical symptoms (fatigue, pain, low sleep quality, indigestion) and mental distress include anxiety, anger, depression. A 21-item quality of healthy measure was developed and tested. We used results of a nation-wide stratified sampled adult data in Korea. Results and Conclusions : Mibyeong index had adequate internal consistency, Cronbach's alpha was 0.88 in general population(N=1,110). The correlation between establised quality of life questionnaires (including SF-12 and EQ-D5 VAS) and the Mibyeong index were from 0.468 to 0.493. The national promotion of advanced health for an aging society and original Mibyeong care technology based on traditional Korean medicine can be developed by a self-care system that enhancing health before suffering illness. We expect that this instrument could be contribute to health management of people in Mibyeong state.